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Objective: This study aimed to compare the predictive value of carotid or femoral artery ultrasound for coronary artery disease (CAD) in type 2 Diabetes mellitus (T2DM) patients free from known CAD, and to assess the relationship with the severity of coronary artery stenosis. Methods: Cross-sectional study in adults with a T2DM duration of at least 5 years and without established CAD. Carotid plaque score (CPS) and Gensini score were used to measure the severity of carotid and coronary artery stenosis, respectively, and patients were divided into no or mild group, moderate group, and severe group according to the tertile of the score. Univariate and multivariate logistic regression analysis was used to explore the possible risk factors for CAD. Receiver operating characteristic (ROC) curves were created to determine the most accurate assessment for detecting significant CAD (≥ 50% stenosis). Results: 245 patients (137 male) aged 68.21± 9.5 years (range: 36– 95 years), with T2DM duration 12.04± 6.17 years (range: 5– 34 years), and without CVD were included. CAD was diagnosed in 165 patients (67.3%). Multiple regression analysis showed that CPS, femoral plaque, and smoking were independently and positively correlated with CAD. CPS yielded the highest area under the curve for detecting significant coronary disease (AUC=0.7323). In contrast, the area under the curve of femoral artery plaque and carotid intima-media thickness was lower than 0.7, which was at a lower prediction level. Conclusion: In patients with long T2DM duration, CPS has a higher ability to predict the occurrence and severity of CAD. However, femoral artery plaque has special value in predicting moderate to severe coronary artery disease in patients with long-term T2DM. [ABSTRACT FROM AUTHOR]

BACKGROUND: Accumulating evidence shows that the increase in blood viscosity (BV) is an independent risk factor for atherosclerosis and its related diseases, but as far as we know, there are few studies on the relationship between blood viscosity and carotid plaque severity. Therefore, we aimed to investigate the relationship between blood viscosity and the presence of carotid plaques, and further explore its relationship with the severity of carotid plaques. METHODS: We retrospectively analyzed the data of consecutive subjects in the physical examination center of the Affiliated Hospital of Ningbo University Medical College from January 2022 to May 2022. The parameters of blood viscosity include the whole blood viscosity (WBV) at high, middle, and low shear rate, plasma viscosity (PV), hematocrit (HCT), rigidity "k", rigidity index (RI), aggregation index (AI) and electrophoresis rate (ER), and standardized BV calculated by Quemada's equation were included in the study. Carotid plaque score (CPS) was used to measure the severity of carotid artery disease, and participants were divided into mild, moderate, and severe groups according to the quartile of the score. Independent samples t-test and one-way ANOVA were used to compare normally distributed continuous variables between two or more independent groups, respectively. Binary logistic regression was used to evaluate the risk factors of carotid plaque. RESULTS: 314 men were enrolled in the study, of which 165 participants were diagnosed with Carotid artery plaque (CAP) (66.9%). Compared with the CAP- group, the WBV and PV of the CAP+group decreased, but the difference only existed in the PV (p = 0.001). However, standardized BV values (HCT set at 0.45) were higher in the CAP+group than in the CAP- group (3.8643±0.35431vs 3.9542±0.64871, p = 0.188). Regarding the rigidity and aggregation of RBC, the parameters including rigidity "k", RI, AI and ER increased in the CAP+group compared with the CAP- group. The difference was statistically significant in k and ER (p = 0.04, p = 0.009). To assess the severity of carotid plaque, we divided the participants into mild, moderate, and severe groups by using the tertile of CPS value. The mild group was defined as CPS≤0.5 (n = 108), the moderate group as 0.5 < CPS≤1.7 (n = 105), and the severe group as CPS > 1.7 (n = 101). It was found that WBV and PV decreased with the increase of plaque severity, but the difference among the three groups was significant in PV (F = 8.073, p < 0.0001). In addition, with the severity of plaque from mild to severe, standardized BV gradually increased, which were 3.8611±0.34845, 3.8757±0.36637, 3.9007±0.38353 respectively. The difference between the groups was close to statistically significant (F = 2.438, p = 0.089). The values of parameters describing erythrocyte aggregation and rigidity increased among the mild, moderate, and severe groups. The difference was statistically significant in RBC rigidity "k" and ER of RBC (F = 3.863, p = 0.022; F = 5.897, p = 0.003, respectively). CONCLUSION: Increased blood viscosity is a risk factor for carotid plaque, but its increase may be hidden by decreased hematocrit. Therefore, it is necessary to comprehensively analyze various parameters of blood viscosity, such as the standardized BV calculated by Quemada's equation, which may provide more useful reference value. [ABSTRACT FROM AUTHOR]

Endothelial nitric oxide synthase (eNOS) is a multifunctional enzyme with roles in diverse cellular processes including angiogenesis, tissue remodeling, and the maintenance of vascular tone. Monomeric and dimeric forms of eNOS exist in various tissues. The dimeric form of eNOS is considered the active form and the monomeric form is considered inactive. The activity of eNOS is also regulated by many other mechanisms, including amino acid phosphorylation and interactions with other proteins. However, the precise mechanisms regulating eNOS dimerization, phosphorylation, and activity remain incompletely characterized. We utilized purified eNOS and bovine aorta endothelial cells (BAECs) to investigate the mechanisms regulating eNOS degradation. Both eNOS monomer and dimer existed in purified bovine eNOS. Incubation of purified bovine eNOS with protein phosphatase 2A (PP2A) resulted in dephosphorylation at Serine 1179 (Ser1179) in both dimer and monomer and decrease in eNOS activity. However, the eNOS dimer∶monomer ratio was unchanged. Similarly, protein phosphatase 1 (PP1) induced dephosphorylation of eNOS at Threonine 497 (Thr497), without altering the eNOS dimer∶monomer ratio. Different from purified eNOS, in cultured BAECs eNOS existed predominantly as dimers. However, eNOS monomers accumulated following treatment with the proteasome inhibitor lactacystin. Additionally, treatment of BAECs with vascular endothelial growth factor (VEGF) resulted in phosphorylation of Ser1179 in eNOS dimers without altering the phosphorylation status of Thr497 in either form. Inhibition of heat shock protein 90 (Hsp90) or Hsp90 silencing destabilized eNOS dimers and was accompanied by dephosphorylation both of Ser1179 and Thr497. In conclusion, our study demonstrates that eNOS monomers, but not eNOS dimers, are degraded by ubiquitination. Additionally, the dimeric eNOS structure is the predominant condition for eNOS amino acid modification and activity regulation. Finally, destabilization of eNOS dimers not only results in eNOS degradation, but also causes changes in eNOS amino acid modifications that further affect eNOS activity. [ABSTRACT FROM AUTHOR]

Aims: The goal of our study is to investigate the combined contribution of 10 genetic variants to diabetes susceptibility. Methods: Bibliographic databases were searched from 1970 to Dec 2012 for studies that reported on genetic association study of diabetes. After a comprehensive filtering procedure, 10 candidate gene variants with informative genotype information were collected for the current meta-anlayses. Using the REVMAN software, odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to evaluate the combined contribution of the selected genetic variants to diabetes. Results: A total of 37 articles among 37,033 cases and 54,716 controls were involved in the present meta-analyses of 10 genetic variants. Three variants were found to be significantly associated with type 1 diabetes (T1D): NLRP1 rs12150220 (OR = 0.71, 95% CI = 0.55–0.92, P = 0.01), IL2RA rs11594656 (OR = 0.86, 95% CI = 0.82–0.91, P<0.00001), and CLEC16A rs725613 (OR = 0.71, 95% CI = 0.55–0.92, P = 0.01). APOA5 −1131T/C polymorphism was shown to be significantly associated with of type 2 diabetes (T2D, OR = 1.27, 95% CI = 1.03–1.57, P = 0.03). No association with diabetes was showed in the meta-analyses of other six genetic variants, including SLC2A10 rs2335491, ATF6 rs2070150, KLF11 rs35927125, CASQ1 rs2275703, GNB3 C825T, and IL12B 1188A/C. Conclusion: Our results demonstrated that IL2RA rs11594656 and CLEC16A rs725613 are protective factors of T1D, while NLRP1 rs12150220 and APOA5 −1131T/C are risky factors of T1D and T2D, respectively. [ABSTRACT FROM AUTHOR]

Abstract: Type 2 diabetes (T2D) and coronary artery disease (CAD) are closely related chronic diseases with high prevalence and morbidity. However, a comprehensive comparison of the two diseases is lacking. Recent genome-wide association studies (GWAS) have identified a handful of single nucleotide polymorphisms (SNPs) that are significantly associated with the risk of T2D and CAD. These most significant findings may help interpret the pathogenesis of T2D and CAD. However, tremendous results from these GWAS are ignored. Here we revisited the raw datasets of these GWAS and performed an integrated gene network analysis to unveil the relationship between T2D and CAD by combining multiple datasets including protein–protein interaction (PPI) database, publication libraries, and pathway datasets. Our results showed that majority of genes were involved in the first module (1122 genes in T2D and 895 in CAD). Four pathways were found to be common in both T2D and CAD, including regulation of actin cytoskeleton, calcium signaling pathway, MAPK signaling pathway and focal adhesion (all P<0.00001). MAX which was involved in small cell lung cancer pathway was a hub gene unique to T2D (OR=1.2, P=0.006) but not in CAD. In contrast, three hub genes including PLEKHG5 (T2D: OR=1, P=1; CAD: OR=1.12, P=0.006), TIAM1 (T2D: OR=1, P=1; CAD: OR=1.48, P=0.004) and AKAP13 (T2D: OR=1, P=1; CAD: OR=1.38, P=0.001) were hub genes unique to CAD. Moreover, for some hub genes (such as SMAD3) that were susceptible to both T2D and CAD, their associated polymorphisms were unique to each of the two diseases. Our findings might provide a landscape of the relationship between T2D and CAD. [Copyright &y& Elsevier]

Renal fibrosis plays a crucial role in the progression of renal diseases, yet the lack of effective diagnostic markers poses challenges in scientific and clinical practices. In this study, we employed machine learning techniques to identify potential biomarkers for renal fibrosis. Utilizing two datasets from the GEO database, we applied LASSO, SVM-RFE and RF algorithms to screen for differentially expressed genes related to inflammatory responses between the renal fibrosis group and the control group. As a result, we identified four genes (CCL5, IFITM1, RIPK2, and TNFAIP6) as promising diagnostic indicators for renal fibrosis. These genes were further validated through in vivo experiments and immunohistochemistry, demonstrating their utility as reliable markers for assessing renal fibrosis. Additionally, we conducted a comprehensive analysis to explore the relationship between these candidate biomarkers, immunity, and drug sensitivity. Integrating these findings, we developed a nomogram with a high discriminative ability, achieving a concordance index of 0.933, enabling the prediction of disease risk in patients with renal fibrosis. Overall, our study presents a predictive model for renal fibrosis and highlights the significance of four potential biomarkers, facilitating clinical diagnosis and personalized treatment. This finding presents valuable insights for advancing precision medicine approaches in the management of renal fibrosis.Communicated by Ramaswamy H. Sarma.

Background: The High Mobility Group Nucleosomal Binding Domain 1 Gene (HMGN1) is crucial for epigenetic regulation. However, the specific function of HMGN1 in cancer development is unclear., Methods: Raw data on HMGN1 expression were procured from Genotype-Tissue Expression (GTEx), the University of Alabama- Birmingham CANcer data analysis Portal (UALCAN), and The Cancer Genome Atlas (TCGA). Thereafter, the pan-cancer analysis was implemented to understand the HMGN1 expression patterns, prognostic value, and immunological features. Furthermore, the Gene Set Enrichment Analysis (GSEA) was executed via R language. In addition, the relationship between HMGN1 and the sensitivity of antitumor drugs was also determined. Finally, real-time PCR (RT-PCR) experiments were carried out., Results: Pan-cancer analysis revealed that HMGN1 was upregulated in several solid tumors and was associated with pathological staging and poor prognosis. In addition, HMGN1 was found to be involved in regulating the tumor microenvironment. The GSEA enrichment analysis indicated that HMGN1 assisted in the regulation of oncogenic processes, especially metabolic and immune pathways. Furthermore, HMGN1 expression was linked to microsatellite instability (MSI) and tumor mutational burden (TMB) across diverse tumor types. RT-PCR assays indicated that HMGN1 was overexpressed in the gastric and breast cancer cell lines and tissues., Conclusion: This study highlighted the potential of HMGN1 as a biomarker for pan- - cancer analysis., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Background: Positive regulators of T cell function play a vital role in the proliferation and differentiation of T cells. However, their functions in gastric cancer have not been explored so far., Methods: The TCGA-STAD dataset was utilized to perform consensus clustering in order to identify subtypes related to T cell-positive regulators. The prognostic differentially expressed genes of these subtypes were identified using the least absolute shrinkage and selection operator (LASSO) regression analysis. To validate the robustness of the identified signature, verification analyses were conducted across the TCGA-train, TCGA-test, and GEO datasets. Additionally, a nomogram was constructed to enhance the clinical efficacy of this predictive tool. Transwell migration, colony formation, and T cell co-culture assays were used to confirm the function of the signature gene in gastric cancer and its influence on T cell activation., Results: Two distinct clusters of gastric cancer, related to T cell-positive regulation, were discovered through the analysis of gene expression. These clusters exhibited notable disparities in terms of survival rates (P = 0.028), immune cell infiltration (P< 0.05), and response to immunotherapy (P< 0.05). Furthermore, a 14-gene signature was developed to classify gastric cancer into low- and high-risk groups, revealing significant differences in survival rates, tumor microenvironment, tumor mutation burden, and drug sensitivity (P< 0.05). Lastly, a comprehensive nomogram model was constructed, incorporating risk factors and various clinical characteristics, to provide an optimal predictive tool. Additionally, an assessment was conducted on the purported molecular functionalities of low- and high-risk gastric cancers. Suppression of DNAAF3 has been observed to diminish the migratory and proliferative capabilities of gastric cancer, as well as attenuate the activation of T cells induced by gastric cancer within the tumor microenvironment., Conclusion: We identified an ideal prognostic signature based on the positive regulators of T cell function in this study., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Guo, Zhang, Cen, Dai, Mai and Hong.)

Background: Inflammation is one of the most important characteristics of tumor tissue. Signatures based on inflammatory response-related genes (IRGs) can predict prognosis and treatment response in a variety of tumors. However, the clear function of IRGs in the triple negative breast cancer (TNBC) still needs to be explored., Methods: IRGs clusters were discovered via consensus clustering, and the prognostic differentially expressed genes (DEGs) across clusters were utilized to develop a signature using a least absolute shrinkage and selection operator (LASSO). Verification analyses were conducted to show the robustness of the signature. The expression of risk genes was identified by RT-qPCR. Lastly, we formulated a nomogram to improve the clinical efficacy of our predictive tool., Results: The IRGs signature, comprised of four genes, was developed and was shown to be highly correlated with the prognoses of TNBC patients. In contrast with the performance of the other individual predictors, we discovered that the IRGs signature was remarkably superior. Also, the ImmuneScores were elevated in the low-risk group. The immune cell infiltration showed significant difference between the two groups, as did the expression of immune checkpoints., Conclusion: The IRGs signature could act as a biomarker and provide a momentous reference for individual therapy of TNBC., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Guo, Cen, Yang, Mai and Hong.)

Background: Recently, the incidence rate of renal fibrosis has been increasing worldwide, greatly increasing the burden on society. However, the diagnostic and therapeutic tools available for the disease are insufficient, necessitating the screening of potential biomarkers to predict renal fibrosis., Methods: Using the Gene Expression Omnibus (GEO) database, we obtained two gene array datasets (GSE76882 and GSE22459) from patients with renal fibrosis and healthy individuals. We identified differentially expressed genes (DEGs) between renal fibrosis and normal tissues and analyzed possible diagnostic biomarkers using machine learning. The diagnostic effect of the candidate markers was evaluated using receiver operating characteristic (ROC) curves and verified their expression using Reverse transcription quantitative polymerase chain reaction (RT-qPCR). The CIBERSORT algorithm was used to determine the proportions of 22 types of immune cells in patients with renal fibrosis, and the correlation between biomarker expression and the proportion of immune cells was studied. Finally, we developed an artificial neural network model of renal fibrosis., Results: Four candidate genes namely DOCK2, SLC1A3, SOX9 and TARP were identified as biomarkers of renal fibrosis, with the area under the ROC curve (AUC) values higher than 0.75. Next, we verified the expression of these genes by RT-qPCR. Subsequently, we revealed the potential disorder of immune cells in the renal fibrosis group through CIBERSORT analysis and found that immune cells were highly correlated with the expression of candidate markers., Conclusion: DOCK2, SLC1A3, SOX9, and TARP were identified as potential diagnostic genes for renal fibrosis, and the most relevant immune cells were identified. Our findings provide potential biomarkers for the diagnosis of renal fibrosis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Guo, Cen, Hong, Mai and Jiang.)

Background: Renal fibrosis is a physiological and pathological characteristic of chronic kidney disease (CKD) to end-stage renal disease. Since renal biopsy is the gold standard for evaluating renal fibrosis, there is an urgent need for additional non-invasive diagnostic biomarkers., Methods: We used R package "limma" to screen out differently expressed genes (DEGs) based on Epithelial-mesenchymal transformation (EMT), and carried out the protein interaction network and GO, KEGG enrichment analysis of DEGs. Secondly, the least absolute shrinkage and selection operator (LASSO), random forest tree (RF), and support vector machine-recursive feature elimination (SVM-RFE) algorithms were used to identify candidate diagnostic genes. ROC curves were plotted to evaluate the clinical diagnostic value of these genes. In addition, mRNA expression levels of candidate diagnostic genes were analyzed in control samples and renal fibrosis samples. CIBERSORT algorithm was used to evaluate immune cells level. Additionally, gene set enrichment analysis (GSEA) and drug sensitivity were conducted., Results: After obtaining a total of 24 DEGs, we discovered that they were mostly involved in several immunological and inflammatory pathways, including NF-KappaB signaling, AGE-RAGE signaling, and TNF signaling. Five genes (COL4A2, CXCL1, TIMP1, VCAM1, and VEGFA) were subsequently identified as biomarkers for renal fibrosis through machine learning, and their expression levels were confirmed by validation cohort data sets and in vitro RT-qPCR experiment. The AUC values of these five genes demonstrated significant clinical diagnostic value in both the training and validation sets. After that, CIBERSORT analysis showed that these biomarkers were strongly associated with immune cell content in renal fibrosis patients. GSEA also identifies the potential roles of these diagnostic genes. Additionally, diagnostic candidate genes were found to be closely related to drug sensitivity. Finally, a nomogram for diagnosing renal fibrosis was developed., Conclusion: COL4A2, CXCL1, TIMP1, VCAM1, and VEGFA are promising diagnostic biomarkers of tissue and serum for renal fibrosis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Guo, Yuan, Hu, Gao, Guo, Zhu, Hong, Cen, Mai, Bai and Yang.)

Reactive oxygen species play a crucial role in the prognosis and tumor microenvironment (TME) of malignant tumors. An ROS-related signature was constructed in gastric cancer (GC) samples from TCGA database. ROS-related genes were obtained from the Molecular Signatures Database. Consensus clustering was used to establish distinct ROS-related subtypes related to different survival and immune cell infiltration patterns. Sequentially, prognostic genes were identified in the ROS-related subtypes, which were used to identify a stable ROS-related signature that predicted the prognosis of GC. Correlation analysis revealed the significance of immune cell iniltration, immunotherapy, and drug sensitivity in gastric cancers with different risks. The putative molecular mechanisms of the different gastric cancer risks were revealed by functional enrichment analysis. A robust nomogram was established to predict the outcome of each gastric cancer. Finally, we verified the expression of the genes involved in the model using RT-qPCR. In conclusion, the ROS-related signature in this study is a novel and stable biomarker associated with TME and immunotherapy responses., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Cen, Wu, Mai, Dai, Hong and Guo.)

Introduction: Cellular senescence is a hallmark of tumors and has potential for cancer therapy. Cellular senescence of tumor cells plays a role in tumor progression, and patient prognosis is related to the tumor microenvironment (TME). This study aimed to explore the predictive value of senescence-related genes in thyroid cancer (THCA) and their relationship with the TME., Methods: Senescence-related genes were identified from the Molecular Signatures Database and used to conduct consensus clustering across TCGA-THCA. Differentially expressed genes (DEGs) were identified between the clusters used to perform multivariate Cox regression and least absolute shrinkage and selection operator regression (LASSO) analyses to construct a senescence-related signature. TCGA dataset was randomly divided into training and test datasets to verify the prognostic ability of the signature. Subsequently, the immune cell infiltration pattern, immunotherapy response, and drug sensitivity of the two subtypes were analyzed. Finally, the expression of signature genes was detected across TCGA-THCA and GSE33630 datasets, and further validated by RT-qPCR., Results: Three senescence clusters were identified based on the expression of 432 senescence-related genes. Then, 23 prognostic DEGs were identified in TCGA dataset. The signature, composed of six genes, showed a significant relationship with survival, immune cell infiltration, clinical characteristics, immune checkpoints, immunotherapy response, and drug sensitivity. Low-risk THCA shows a better prognosis and higher immunotherapy response than high-risk THCA. A nomogram with perfect stability constructed using signature and clinical characteristics can predict the survival of each patient. The validation part demonstrated that ADAMTSL4, DOCK6, FAM111B, and SEMA6B were expressed at higher levels in the tumor tissue, whereas lower expression of MRPS10 and PSMB7 was observed., Discussion: In conclusion, the senescence-related signature is a promising biomarker for predicting the outcome of THCA and has the potential to guide immunotherapy., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Hong, Cen, Chen, Dai, Mai and Guo.)

Background: It is well known that the prognosis of Gastric cancer (GC) patient is affected by many factors. However, the latent impact of anoikis on the prognosis of GC patients is insufficient understood., Methods: According to the Cancer Genome Atlas (TCGA) database, we elected discrepantly expressed anoikis-related genes (ARGs). Univariate cox and the least absolute shrinkage and selection operator (lasso) analysis were applied to build the ARGs signature. The prognostic effect of the ARGs signature was also evaluated. A series of algorithms were performed to evaluate the discrepancies in the immune microenvironment. Moreover, the correlation between drug sensitivity and ARGs signature was analyzed. We also performed Real-Time Polymerase Chain Reaction (RT-PCR) to probe the signature., Results: The ARGs signature of 9 genes was constructed, which was apparently interrelated with the prognosis. The nomogram was established by combining the ARGs signature with clinicopathological characteristics. We found that the predictive power was noteworthily superior to other individual predictors. The immune microenvironment analysis indicated that ESTIMATEscore, ImmuneScores, StromalScores, tumor immune dysfunction and exclusion (TIDE) score were lower in the low-risk group, while immunophenoscore (IPS) was on the contrary. The infiltrated immune cells and immune checkpoint (ICP) expression levels were significantly different between the two groups. Furthermore, nine drugs were positively associated with the ARGs signature score. The results of RT-PCR analysis were consistent with our previous differential expression analysis., Conclusion: The developed ARGs signature could act as the biomarker and provide a momentous reference for Individual therapy of GC patients., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Cao, Hong, Cao, Cen, Mai, Dai, Ouyang, Mu and Guo.)

Breast cancer (BC) is one of the most common tumor types and has poor outcomes. In this study, a ubiquitination-related prognostic signature was constructed, and its association with immunotherapy response in BC was explored. A list of ubiquitination-related genes was obtained from the molecular signatures database, and a ubiquitination-related gene signature was obtained by least absolute shrinkage and selection operator Cox regression. The genes, TCN1 , DIRAS3 , and IZUMO4 , had significant influence on BC outcomes. Patients were categorized into two clusters-a high-risk group with poor survival and a low-risk group with greater chances of controlling BC progression. Univariate and multivariate Cox regression analyses revealed that the risk signature was an independent prognostic factor for BC. Gene set enrichment analysis suggested that the high-risk group was enriched in cell cycle and DNA replication pathways. The risk score was positively linked to the tumor microenvironment and negatively correlated with the immunotherapy response. The IC50 values for rapamycin were higher in the low-risk group, whereas those for axitinib, AZD6244, erlotinib, GDC0941, GSK650394, GSK269962A, lapatinib, and PD0325901 were higher in the high-risk group. Therefore, the ubiquitination-related signature is considered a promising tool for predicting a BC patient's immunotherapy response., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Hong, Chen, Zhang, Cheng, Cen, Dai, Mai and Guo.)

The present study aimed to investigate the contribution of DNA methylation of the protein tyrosine phosphatase, non-receptor type 1 ( PTPN1 ) gene to the susceptibility to type 2 diabetes (T2D). Peripheral blood mononuclear cells (PBMCs) were collected from 97 patients with T2D and 97 age- and gender-matched controls. DNA methylation of the PTPN1 gene promoter was evaluated by bisulfite pyrosequencing. Independent sample t-tests were used to compare the differences in the PTPN1 promoter and other phenotypes between the patients with T2D and the controls. The results indicated a significant correlation between PTPN1 promoter methylation and the risk of T2D. Additionally, a breakdown analysis by gender revealed that PTPN1 methylation was associated with an increased risk of T2D in females. Furthermore, low-density lipoprotein (r=-0.183, P=0.046) and total cholesterol (r=-0.310, P=0.001) were inversely associated with PTPN1 methylation in females. In conclusion, the results indicate that elevated PTPN1 promoter methylation is a risk factor for T2D in the female Chinese population.

Associations between insulin-like growth factor 2 mRNA-binding protein 2 ( IGF2BP2 ) rs11705701, insulin receptor substrate 1 rs7578326, gastric inhibitory polypeptide receptor rs10423928 and transcription factor 7-like 2 rs12255372 gene polymorphisms with prediabetes and type 2 diabetes (T2D) have not been evaluated in the Han Chinese population. These four genetic variants were investigated for their associations with prediabetes and T2D among 490 unrelated patients with T2D, 471 patients with prediabetes and 575 healthy controls. Sequenom MassARRAY software was used to genotype the patients for these variants. The Generalized Multifactor Dimensionality Reduction method was used to analyze the gene-gene and gene-environment interactions. A breakdown analysis by gender revealed a significant association of IGF2BP2 rs11705701 with prediabetes under the dominant genetic model in females following application of the Bonferroni correction (odds ratio = 0.26; 95% confidence interval = 0.10-0.67; P=0.005). However, no significant associations were reported between any of the other three polymorphisms and T2D under any genetic models. Furthermore, there were no statistically significant gene-gene or gene-environment interactions when evaluated with the above association tests. The present case-control study reveals a significant association between IGF2BP2 rs11705701 and prediabetes in female patients.

Objective: Despite of the common usage of glucocorticoids (GCs), a significant portion of asthma patients exhibit GC insensitivity. This could be mediated by diverse mechanisms, including genomics. Recent work has suggested that measuring changes in gene expression may provide more predictive information about GC insensitivity than baseline gene expression alone, and that expression changes in peripheral blood may be reflective of those in the airway., Methods: We performed in silico discovery using gene expression omnibus (GEO) data that evaluated GC effect on gene expression in multiple tissue types. Subsequently, candidate genes whose expression levels are affected by GC were examined in cell lines and in primary cells derived from human airway and blood., Results: Through gene expression omnibus analysis, we identified interferon regulator factor 1 (IRF1), whose expression is affected by GC treatment in airway smooth muscle cells, normal human bronchial epithelial (NHBE) cells, and lymphoblastoid cell lines (LCLs). Significant IRF1 downregulation post GC exposure was confirmed in two cultured airway epithelial cell lines and primary NHBE cells (P<0.05). We observed large interindividual variation in GC-induced IRF1 expression changes among primary NHBE cells tested. Significant downregulation of IRF1 was also observed in six randomly selected LCLs (P<0.05), with variable degrees of downregulation among different samples. In peripheral blood mononuclear cells obtained from healthy volunteers, variable downregulation of IRF1 by GC was also shown. NFKB1, a gene whose expression is known to be downregulated by GC and the degree of downregulation of which is reflective of GC response, was used as a control in our study. IRF1 shows more consistent downregulation across tissue types when compared with NFKB1., Conclusion: Our results suggest that GC-induced IRF1 gene expression changes in peripheral blood could be used as a marker to reflect GC response in the airway.

The association of the fat mass and obesity-associated gene ( FTO ) rs11642015 polymorphism with prediabetes, type 2 diabetes and obesity in certain populations has not been previously reported. A population-based study was conducted that included 490 type 2 diabetic, 471 prediabetic and 575 normal subjects. The main outcomes of the study were prediabetes, type 2 diabetes and obesity. Binary logistic regression was performed to estimate the association of FTO rs11642015 with the risk of prediabetes, type 2 diabetes and obesity following adjustment for the corresponding confounders. A meta-analysis was also conducted to evaluate the association between FTO rs11642015 and obesity. FTO rs11642015 was significantly associated with prediabetes in the whole sample under the additive model [odds ratio (OR), 1.50; 95% confidence interval (CI), 1.17-1.93; P=0.002], particularly in females. The polymorphism remained consistently significant following adjustment for age and body mass index (BMI), showing an increased prediabetes risk with an additive effect (OR, 1.55; 95% CI, 1.19-2.01; P=0.001). In addition, a significant association was found for rs11642015 with prediabetes and type 2 diabetes under the dominant model. However, under the stringent Bonferroni's correction there was no evidence of positive associations for FTO rs11642015 with obesity in the whole sample, females or males. Findings of the meta-analysis showed that FTO rs11642015 was not predisposed to obesity. In conclusion, the T allele of FTO rs11642015 is positively associated with an increased risk of prediabetes, even after adjustment for age and BMI, particularly in females. Subjects carrying the CT + TT genotype are predisposed to prediabetes and type 2 diabetes. Therefore, results of the population-based study and follow-up meta-analysis suggested that FTO rs11642015 is not significantly associated with susceptibility to obesity.

Background: The GCK gene encodes hexokinase 4, which catalyzes the first step in most glucose metabolism pathways. The purpose of our study is to assess the contribution of GCK methylation to type 2 diabetes (T2D)., Methods and Results: GCK methylation was evaluated in 48 T2D cases and 48 age- and gender-matched controls using the bisulphite pyrosequencing technology. Among the four CpG sites in the methylation assay, CpG4 and the other three CpGs (CpG1-3) were not in high correlation (r<0.5). Significantly elevated methylation levels of GCK CpG4 methylation were observed in T2D patients than in the healthy controls (P=0.004). A breakdown analysis by gender indicated that the association between CpG4 methylation and T2D was specific to males (P=0.002). It is intriguing that another significant male-specific association was also found between GCK CpG4 methylation and total cholesterol (TC) concentration (r=0.304, P=0.036)., Conclusion: Our results showed that elevated GCK CpG4 methylation might suggest a risk of T2D in Chinese males. Gender disparity in GCK CpG4 methylation might provide a clue to elaborate the pathogenesis of T2D., (Copyright © 2014 Elsevier B.V. All rights reserved.)

BCL11A is a critical modulator involved in hemoglobin switching. Recent studies have established an association between BCL11A gene polymorphisms and a risk of type 2 diabetes (T2D). The aim of the present study was to assess the correlation between BCL11A DNA methylation and T2D. A total of 48 T2D cases and 48 age- and gender-matched controls were recruited to evaluate BCL11A methylation using bisulfite pyrosequencing technology. Although no significant association was observed in BCL11A methylation between T2D patients and healthy controls (P=0.322), breakdown analysis by gender identified a significant association between BCL11A methylation and T2D in males (P=0.018). Notably, there was also a significant female-specific association between the mean BCL11A DNA methylation and triglyceride (TG) concentration (r=-0.34; P=0.019). The results indicated that BCL11A methylation contributed to the risk of T2D in males. In addition, BCL11A methylation may have an effect on the development of T2D by influencing TG metabolism. Thus, gender difference may provide new information to aid the understanding of T2D pathogenesis.

Aims: The goal of our study is to investigate the associations between 18 candidate genetic markers and overweight/obesity., Methods: A total of 72 eligible articles were retrieved from literature databases including PubMed, Embase, SpingerLink, Web of Science, Chinese National Knowledge Infrastructure (CNKI), and Wanfang. Meta-analyses of 18 genetic markers among 56,738 controls and 48,148 overweight/obese persons were done by Review Manager 5.0., Results: Our results showed that SH2B1 rs7498665 polymorphism was significantly associated with the risk of overweight/obesity (overall odds ratio (OR) = 1.21, 95% confidence interval (CI) = 1.09-1.34, P = 0.0004). Increased risk of overweight/obesity was also observed in FAIM2 rs7138803 polymorphism (overall OR = 1.11, 95% CI = 1.01-1.22, P = 0.04)., Conclusion: Our meta-analyses have shown the important role of 2 polymorphisms (SH2B1 rs7498665 and FAIM2 rs7138803) in the development of overweight/obesity. This study highlighted the importance of above two candidate genes (SH2B1 and FAIM2) in the risk of overweight/obesity., Virtual Slides: The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/2785487401176182.

Background: Controversy remains for the association between hepatocyte nuclear factor 4α (HNF-4α) P2 promoter polymorphism rs1884613 and type 2 diabetes (T2D). There was no association test of this polymorphism with prediabetes and T2D in the Chinese population. Moreover, an updated meta-analysis in various ethnic groups is needed to establish the contribution of rs1884613 to T2D risk., Methods: Using the Sequenom MassARRAY platform approach, we genotyped rs1884613 of HNF-4α in the P2 promoter region among 490 T2D patients, 471 individuals with prediabetes, and 575 healthy controls. All the individuals were recruited from 16 community health service centers in Nanshan district in Shenzhen province. Using STATA 11.0 software, meta-analysis was performed to summarize the overall contribution of rs1884613 to T2D risk., Results: Polymorphism rs1884613 was associated with genetic susceptibility to prediabetes in the whole samples (OR = 1.40, 95% CI = 1.16-1.68, P = 0.0001) and the female subgrouped samples (OR = 1.48, 95% CI = 1.14-1.92, P = 0.003) after adjusting for age and body mass index (BMI). In contrast, there was no association of rs1884613 with T2D in the whole samples and male in our case-control study and meta-analysis., Conclusions: Our results suggest that rs1884613 contributes to susceptibility to prediabetes, whereas this polymorphism may not play an important role in the development of T2D.